################## # Performance Model Version 45 #################### # COMBs # number of combinations 4 #################### # COMB_3 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3) 0 #################### # DEV_0 # device id 0 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cpu0_impl0 (Comb3) # number of entries 3 # sumlnx sumlnx2 sumlny sumlnxlny alpha beta n minx maxx 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 nan nan 0 0 0 # a b c nan nan nan # not multiple-regression-base 0 # hash size flops mean (us) dev (us) sum sum2 n 617e5fe6 7372800 0.000000e+00 2.515766e+05 2.096151e+04 2.515766e+06 6.373017e+11 10 afdd228b 3276800 0.000000e+00 7.350482e+04 4.292777e+03 9.555626e+05 7.047802e+10 13 cea37d6d 819200 0.000000e+00 9.586125e+03 1.023620e+03 2.108948e+05 2.044715e+09 22 #################### # COMB_1 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3) 1 #################### # DEV_0 # device id 0 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda0_impl0 (Comb1) # number of entries 3 # sumlnx sumlnx2 sumlny sumlnxlny alpha beta n minx maxx 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 nan nan 0 0 0 # a b c nan nan nan # not multiple-regression-base 0 # hash size flops mean (us) dev (us) sum sum2 n 617e5fe6 7372800 0.000000e+00 6.990473e+04 4.071360e+03 1.118476e+06 7.845196e+10 16 afdd228b 3276800 0.000000e+00 2.992444e+04 7.760944e+02 4.787910e+05 1.433719e+10 16 cea37d6d 819200 0.000000e+00 9.620220e+03 2.335102e+02 1.058224e+05 1.018635e+09 11 #################### # COMB_0 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3) 1 #################### # DEV_0 # device id 1 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda1_impl0 (Comb0) # number of entries 3 # sumlnx sumlnx2 sumlny sumlnxlny alpha beta n minx maxx 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 nan nan 0 0 0 # a b c nan nan nan # not multiple-regression-base 0 # hash size flops mean (us) dev (us) sum sum2 n 617e5fe6 7372800 0.000000e+00 6.793522e+04 8.600858e+02 6.793522e+05 4.615934e+10 10 afdd228b 3276800 0.000000e+00 2.989699e+04 1.490344e+03 3.587638e+05 1.075261e+10 12 cea37d6d 819200 0.000000e+00 9.974140e+03 1.055336e+03 1.097155e+05 1.106569e+09 11 #################### # COMB_2 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3) 1 #################### # DEV_0 # device id 2 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda2_impl0 (Comb2) # number of entries 3 # sumlnx sumlnx2 sumlny sumlnxlny alpha beta n minx maxx 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 nan nan 0 0 0 # a b c nan nan nan # not multiple-regression-base 0 # hash size flops mean (us) dev (us) sum sum2 n 617e5fe6 7372800 0.000000e+00 6.962168e+04 1.952172e+02 1.322812e+06 9.209711e+10 19 afdd228b 3276800 0.000000e+00 3.047853e+04 4.777511e+01 4.571780e+05 1.393415e+10 15 cea37d6d 819200 0.000000e+00 1.119488e+04 2.171263e+03 1.231437e+05 1.430437e+09 11